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We have 9 Statistics (cancer) PhD Projects, Programmes & Scholarships

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Statistics (cancer) PhD Projects, Programmes & Scholarships

We have 9 Statistics (cancer) PhD Projects, Programmes & Scholarships

Repurposing and enriching cardiovascular risk prediction model to identify people at risk of cancer – UCL (part of Health Data Research UK’s Big Data for Complex Disease Driver Programme)

Risk-stratified management of cardiovascular disease (CVD), where people without established disease receive preventative interventions and monitoring based on their 10-years predicted risk, has been highly successful to ensure healthcare resources are allocated to those most likely to benefit. Read more

Statistical ‘omics on graphs

  Research Group: Division of Statistics
The field of statistical genomics (and related omics) is rapidly accepting that graphical models have a role to play in addressing the complexity of the molecular systems being investigated. Read more

Propagation of uncertainty for signatures of mutational processes

  Research Group: Division of Statistics
There is a trend, especially in cancer research, to i) take a set of DNA mutations ii) cross-categorize them by patient and mutational characteristic and iii) decompose the resulting counts matrix into two sets of vectors – one set representing the mutational impact of specific mutagens and one set representing the exposure of individuals to those mutagens. Read more

Noise and Evolution in Ageing Cellular Power Stations

PhD Project. Imperial College Mathematics. Student Background. Theoretical Physics, Mathematics/Statistics, Electrical Engineering, Computing (Biological knowledge not required). Read more

Exploring synergies between statistical ecology and statistical genomics

  Research Group: Division of Statistics
While superficially different, these two areas of research share several questions in common (How many species? How many of each species? How are the species distributed spatially? How should we sample?) that differ fundamentally only in whether the species in question are flora and fauna or nucleic acids and proteins. Read more

Incorporating Mixture of Expert Models for Longitudinal Data with Missing and Censoring

  Research Group: Division of Statistics
Longitudinal data analysis is a powerful tool for studying changes in subjects over time. However, the presence of missing data and censoring poses significant challenges. Read more
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